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   "source": [
    "import pandas as pd\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from sklearn.preprocessing import LabelEncoder\n",
    "from sklearn.preprocessing import OneHotEncoder,Binarizer\n",
    "from sklearn.model_selection import train_test_split\n",
    "import numpy as np\n",
    "from sklearn.linear_model import LogisticRegression,LinearRegression\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.tree import DecisionTreeClassifier\n",
    "from sklearn.metrics import accuracy_score,confusion_matrix,mean_squared_error,recall_score,roc_auc_score,precision_score,f1_score\n",
    "from sklearn.model_selection import GridSearchCV\n",
    "import joblib\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.metrics import classification_report\n",
    "from sklearn.metrics import RocCurveDisplay\n",
    "from sklearn import metrics\n",
    "from sklearn.metrics import precision_recall_curve\n",
    "from sklearn.feature_extraction.text import CountVectorizer,TfidfVectorizer\n",
    "import jieba\n",
    "from sklearn.cluster import KMeans\n",
    "from sklearn.impute import SimpleImputer\n",
    "from xgboost import XGBRegressor\n",
    "from xgboost import XGBClassifier\n",
    "from sklearn.ensemble import GradientBoostingRegressor\n",
    "from sklearn.metrics import r2_score, mean_absolute_error\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "outputs": [
    {
     "data": {
      "text/plain": "     年龄(岁)  收入(万元)\n0       50      66\n1       44      51\n2       30      56\n3       46      50\n4       32      50\n..     ...     ...\n107     30      30\n108     32      29\n109     24      18\n110     24      15\n111     25      40\n\n[112 rows x 2 columns]",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>年龄(岁)</th>\n      <th>收入(万元)</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>50</td>\n      <td>66</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>44</td>\n      <td>51</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>30</td>\n      <td>56</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>46</td>\n      <td>50</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>32</td>\n      <td>50</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>107</th>\n      <td>30</td>\n      <td>30</td>\n    </tr>\n    <tr>\n      <th>108</th>\n      <td>32</td>\n      <td>29</td>\n    </tr>\n    <tr>\n      <th>109</th>\n      <td>24</td>\n      <td>18</td>\n    </tr>\n    <tr>\n      <th>110</th>\n      <td>24</td>\n      <td>15</td>\n    </tr>\n    <tr>\n      <th>111</th>\n      <td>25</td>\n      <td>40</td>\n    </tr>\n  </tbody>\n</table>\n<p>112 rows × 2 columns</p>\n</div>"
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     "execution_count": 2,
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   "source": [
    "df = pd.read_excel(\"C:\\\\Users\\\\Administrator\\\\Desktop\\\\月考练习算法题 (2)\\\\月考练习算法题\\\\第6套（修改2）\\\\专高6月考-06附件\\\\客户信息.xlsx\")\n",
    "df\n"
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